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Mantas Bacevicius and Agne Paulauskaite-Taraseviciene
Various machine learning algorithms have been applied to network intrusion classification problems, including both binary and multi-class classifications. Despite the existence of numerous studies involving unbalanced network intrusion datasets, such as ...
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Yefang Sun, Jun Gong and Yueyi Zhang
Data imbalance is a common problem in classification tasks. The Mahalanobis-Taguchi system (MTS) has proven to be promising due to its lack of requirements for data distribution. The MTS is a binary classifier. However, multi-classification problems are ...
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Jinfu Liu, Mingliang Bai, Na Jiang, Ran Cheng, Xianling Li, Yifang Wang and Daren Yu
Multi-classifiers are widely applied in many practical problems. But the features that can significantly discriminate a certain class from others are often deleted in the feature selection process of multi-classifiers, which seriously decreases the gener...
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Renato Bruni, Gianpiero Bianchi and Pasquale Papa
User requests to a customer service, also known as tickets, are essentially short texts in natural language. They should be grouped by topic to be answered efficiently. The effectiveness increases if this semantic categorization becomes automatic. We pur...
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Zafar Mahmood, Naveed Anwer Butt, Ghani Ur Rehman, Muhammad Zubair, Muhammad Aslam, Afzal Badshah and Syeda Fizzah Jilani
The classification of imbalanced and overlapping data has provided customary insight over the last decade, as most real-world applications comprise multiple classes with an imbalanced distribution of samples. Samples from different classes overlap near c...
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Gábor Kertész
Image based instance recognition is a difficult problem, in some cases even for the human eye. While latest developments in computer vision?mostly driven by deep learning?have shown that high performance models for classification or categorization can be...
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Li-Na Wang, Hongxu Wei, Yuchen Zheng, Junyu Dong and Guoqiang Zhong
Ensemble learning, online learning and deep learning are very effective and versatile in a wide spectrum of problem domains, such as feature extraction, multi-class classification and retrieval. In this paper, combining the ideas of ensemble learning, on...
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Priyadarshni Suresh Sagar, Eman Abdulah AlOmar, Mohamed Wiem Mkaouer, Ali Ouni and Christian D. Newman
Understanding how developers refactor their code is critical to support the design improvement process of software. This paper investigates to what extent code metrics are good indicators for predicting refactoring activity in the source code. In order t...
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Retno Kusumaningrum, Titan A. Indihatmoko, Saesarinda R. Juwita, Alfi F. Hanifah, Khadijah Khadijah and Bayu Surarso
Stunting is a condition in which children experience impaired growth and development, caused by malnutrition, repeated infections, and inadequate psychosocial stimulation. It often remains unrecognized due to a lack of awareness in the community. Therefo...
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Mustafa Pamuk and Matthias Schumann
Corporate credit ratings provide multiple strategic, financial, and managerial benefits for decision-makers. Therefore, it is essential to have accurate and up-to-date ratings to continuously monitor companies? financial situations when making financial ...
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Sergey A. Soldatov, Danil M. Pashkov, Sergey A. Guda, Nikolay S. Karnaukhov, Alexander A. Guda and Alexander V. Soldatov
Microscopic tissue analysis is the key diagnostic method needed for disease identification and choosing the best treatment regimen. According to the Global Cancer Observatory, approximately two million people are diagnosed with colorectal cancer each yea...
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A.N. Alpatov,K.S. Popov,A.N. Chesalin
Pág. 47 - 53
This paper investigates the problem of natural language processing using machine learning techniques, in particular, classification of unstructured heterogeneous text data sets. The paper presents a comparative analysis of some relevant and widely used m...
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A.N. Alpatov,K.S. Popov,A.N. Chesalin
Pág. 47 - 53
This paper investigates the problem of natural language processing using machine learning techniques, in particular, classification of unstructured heterogeneous text data sets. The paper presents a comparative analysis of some relevant and widely used m...
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Nikola Andelic, Ivan Lorencin, Sandi Baressi ?egota and Zlatan Car
Hepatitis C is an infectious disease which is caused by the Hepatitis C virus (HCV) and the virus primarily affects the liver. Based on the publicly available dataset used in this paper the idea is to develop a mathematical equation that could be used to...
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